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Safety Intelligence API

Plug predictive risk scores, route analysis, and citywide forecasting directly into your tools - over a secure API.

Safety Intelligence API Lab
SandboxReady

Request builder

Mock

Location

Selected coordinatesClick map to run
-26.2041, 28.0473

Endpoint

/predict

Point-based risk score

POST https://api.your-domain.com/v1/predict
Authorization: Bearer sk_sia_••••••
Content-Type: application/json
{
  "lat": -26.2041,
  "lng": 28.0473,
  "date": "2026-02-07",
  "horizon_days": 7,
  "categories": "ALL",
  "include_breakdown": true
}
Request SIA-0042
Last run -

Click the map or run the request to generate fresh results.

Response

Awaiting request

-
Preview responseClick to load
Safety grid
Drag to explore
Click to run a request here
Hotspots 3
Loading risk map…

One API for real-time safety intelligence

You dropped a pin on the map above and got back a risk score. That is the Safety Intelligence API - real-time and predictive location risk, available to any application, platform, or operations team through standard REST endpoints. Submit a coordinate. Score a route. Pull a city-wide forecast. All authenticated with a single API key.

Safety data today is fragmented, delayed, and hard to use

Understanding the safety profile of a location currently means stitching together quarterly government reports, informal community channels, and proprietary guesswork. None of these sources talk to each other. Crime statistics are months old before they reach a spreadsheet. Community-reported incidents live in WhatsApp groups with no structure. Emergency logs stay locked inside isolated control rooms.

For insurers pricing risk, logistics operators planning routes, property platforms surfacing neighbourhood data, and city planners allocating resources - the dataset they need either does not exist or cannot be queried programmatically.

What powers it

Millions of safety signals, structured into one dataset

The Safety Intelligence API draws on millions of geo-tagged safety events - community-reported incidents, verified emergency responses, access control logs, and patrol activity - aggregated and structured into a continuously learning safety graph. Raw, siloed signals become standardised, queryable risk intelligence.

This is not a static crime database. As new signals arrive, the models retrain and the intelligence sharpens. The result is a living dataset that reflects what is happening now, not what happened last quarter.

Location risk

Drop a pin, get a risk score

Send any latitude and longitude. Receive a probability distribution across six standardised crime categories and a single composite risk score - in milliseconds.

Route scoring

Score a journey before it starts

Submit a planned route and get segment-by-segment risk scoring. Dispatch teams, logistics operators, and travel planners see high-risk stretches before anyone moves.

City forecasting

Predict risk before it arrives

Run batch predictions across a city grid to power heatmaps, scheduled briefings, and automated alerts - with a forecast horizon of up to 40 weeks.

Built for teams that depend on location risk

Insurance and underwriting

Price policies with real-time risk scores rather than annual static datasets.

Mobility and logistics

Score delivery routes, ride-hail corridors, and driver allocation zones before dispatch.

Property and real estate

Surface verified safety profiles alongside listings instead of anecdotal neighbourhood ratings.

Private security

Optimise patrol coverage, benchmark response areas, and brief teams with predictive intelligence.

City and public sector

Monitor hotspots, measure intervention impact, and allocate resources based on predicted risk.

Mapping and navigation

Embed safety layers into existing map products without building the data pipeline yourself.

How it works

Standardised risk categories

Every response returns probabilities across six crime categories. They sum to 1.0 and roll up into a single composite score - so you can filter, sort, and threshold without building custom models.

  • THEFT_BURGLARYProperty theft and burglary
  • BATTERY_ASSAULTAssault and battery
  • VEHICLE_DAMAGEVehicle damage and theft
  • SERIOUS_VIOLENTHigh-severity violent crime
  • OTHERAll other incident types
  • NO_CRIMENo crime predicted

Example response

{
"location": { "lat": -33.9249, "lng": 18.4241 },
"timestamp": "2026-02-07T18:00:00Z",
"categories": {
  "THEFT_BURGLARY": 0.31,
  "BATTERY_ASSAULT": 0.18,
  "VEHICLE_DAMAGE": 0.12,
  "SERIOUS_VIOLENT": 0.07,
  "OTHER": 0.09,
  "NO_CRIME": 0.23
},
"risk_score": 0.68
}

Probabilities sum to 1.0. The composite risk score is weighted from category values.

Coverage

10 cities across 3 continents

Johannesburg, Cape Town, Durban, London, Chicago, Los Angeles, San Francisco, New York City, Boston, and Philadelphia - with new cities added as datasets are verified.

  • H3 hexagonal grid for consistent spatial resolution.
  • Auto-routing to the nearest supported city.
  • Sub-10ms response targets on production tiers.

Model performance

Trained on real-world safety data

The prediction model uses a spatial convolutional network with temporal features, trained on verified incidents and continuously retrained as new signals arrive.

  • 71.1% accuracy, F1 0.697 on internal benchmarks.
  • MAE 3.82%, Brier score 0.0355.
  • Forecast horizon up to 40 weeks ahead.

See the Safety Intelligence API in action

Book a demo to review endpoints, coverage, and pricing. The API is available in sandbox, partner, and enterprise tiers with bearer token authentication, tiered rate limits, and audit logging.

Book a demoRequest API access

Prefer to self-serve?

Read the API docs

.